CN-121995864-A - Intelligent control system and control method for station

CN121995864ACN 121995864 ACN121995864 ACN 121995864ACN-121995864-A

Abstract

The invention relates to the technical field of intelligent control of stations, in particular to an intelligent control system of stations, which comprises equipment fault self-detection, module linkage control, intelligent flow switching, intelligent emergency stop regulation and control and management; according to the intelligent control system for the combined station, through equipment fault self-detection, module linkage control, intelligent flow switching and intelligent emergency stop regulation and control technology, the labor consumption of the combined station is reduced from 20-30 persons to 5-10 persons, automatic task execution, abnormal automatic alarm and automatic report generation are realized through intelligent inspection, manual regular station inspection is replaced, the stay frequency and time of workers in a production area with a large number of dangerous sources are reduced, the running state of the station is intuitively displayed on a computer in a graphic form, important parameters of each instrument are accessed, remote check and alarm reminding can be realized, the running parameters of each key equipment can be randomly checked and inquired on a dot graph in time, and analysis of current running data and historical running data is included.

Inventors

ZHANG RUI
MA SHIQING
YANG QIAN
HE ZHANYOU
ZHANG LIANG
WEI LEI
XIA XING
SONG TAO

Assignees

中国石油天然气股份有限公司

Dates

Publication Date: 20260508
Application Date: 20241108

Claims (10)

1. The intelligent station control system is characterized by comprising equipment fault self-detection, module linkage control, intelligent flow switching, intelligent emergency stop regulation and control and management; The equipment fault self-checking comprises a data acquisition module, a fault diagnosis module and a solution module, wherein the data acquisition module acquires relevant operation data from equipment through the acquisition equipment, the fault diagnosis module analyzes and processes the acquired data, ‌ is combined with a preset fault model and algorithm, ‌ is used for diagnosing and positioning equipment fault reasons, the fault model comprises a support vector machine, a decision tree, a random forest or a neural network, and the mathematical model formula of the support vector machine is as follows , Representing a decision function, Is a parameter of a support vector machine, Is a sample label, Is a kernel function, b is an offset, x is an input vector, and the decision tree mathematical model formula is if Wherein Is an input variable, Is an output variable, Representing category, c representing category number, and a random forest mathematical model formula is , Representing the predicted result of the random forest on the input data x, Representing the number of decision trees in a random forest, Represent the first The result of the prediction of the decision tree is expressed as a neural network formula , Representing the output of neurons, Representing an activation function, Represent the first The weight of each input signal, Represent the first The fault diagnosis method comprises rule-based diagnosis, ‌ model-driven diagnosis and data mining-based diagnosis, wherein a solution and suggestion library is preset in a solution module, and corresponding solutions and suggestions are provided according to the fault diagnosis result ‌, and ‌ is provided for a user to refer to and take corresponding repair measures; The module linkage control comprises a control module, a data storage processing module, a communication module and a human-computer interface, wherein the control module is used for executing control instructions to adjust the running state of equipment, the data storage processing module is used for storing and processing collected data, and comprises a database and a data server, the communication module is used for realizing data transmission between internal equipment and external equipment, and the human-computer interface is used for interaction between operators and the equipment and comprises a display screen, a control panel and a touch screen; The intelligent flow switching comprises a field control station, a document management and hardware equipment, wherein the field control station is responsible for monitoring and controlling various equipment and flows in the field station in real time, the document management is used for sorting, ‌ induction and statistics of various document materials generated in the whole life cycle of equipment, ‌ supports the inquiry and browsing of document intensive, ‌ multi-level and ‌ different structures, and the hardware equipment comprises, but is not limited to, a converter valve, a ‌ direct current filter and an alternating current filter; The emergency stop intelligent regulation and control comprises emergency stops ‌, ‌, an electric actuating mechanism of emergency stop valves ‌ and ‌ and a ‌ uninterruptible power supply device, wherein the emergency stops ‌ are used for immediately and emergently stopping ‌ when a serious accident occurs in a station or a downstream pipeline, ‌ separates the upstream pipeline and the downstream pipeline from the station, ‌ is used for reducing the loss of natural gas in an accident state and protecting the safety of the station, the emergency stop valve ‌ is matched with the emergency stops for use, the ‌ realizes quick stop through the electric actuating mechanism, ‌ is used for preventing the expansion of the accident, the electric actuating mechanism is powered by the uninterruptible power supply device ‌, ‌ ensures that the electric actuating mechanism can still operate under the condition of power failure, ‌ ensures the normal operation of the emergency stop valve, and the uninterruptible power supply device ‌ provides continuous power supply for the electric actuating mechanism, and ‌ ensures the reliable operation under the emergency condition; The management comprises system management, equipment management, station management and remote control, wherein the system management comprises department management, user management, role management and post management, the equipment management comprises equipment information management and equipment grouping, the station management comprises station overview, station file management, line management, station configuration, real-time data, early warning data and historical data, and the remote control is used for controlling the on or off of equipment.
2. The intelligent control system of claim 1, wherein the acquisition devices include, but are not limited to, sensors, ‌ meters, ‌ image acquisition devices, ‌ sound acquisition devices, ‌ GPS positioning devices, ‌ RFID tag devices, ‌ data acquisition terminals, ‌ smart phones, and handheld terminals.
3. The intelligent control system for a station according to claim 1, wherein the fault model is established by the steps of: (1) Collecting data; (2) Cleaning and preprocessing data; (3) Selecting a feature related to the fault from the preprocessed data as an input variable; (4) Training by using the selected characteristics and known fault data through a machine learning algorithm to obtain a model for predicting fault occurrence; (5) Verifying the trained model, and evaluating the prediction effect of the model on new data; (6) Setting a corresponding early warning threshold value; (7) The trained model is applied to actual equipment, so that real-time monitoring is realized; (8) Model updates and optimizations are performed periodically.
4. The intelligent control system according to claim 1, wherein the control module comprises a programmable logic controller and a remote terminal unit.
5. The intelligent control system according to claim 1, wherein the database functions include data storage and management, data query, data processing, data security, data backup and recovery, concurrency control, and transaction management.
6. The intelligent control system according to claim 1, wherein the communication module comprises wired communication and wireless communication, wherein the wired communication adopts Ethernet and/or optical fiber, and the wireless communication adopts GPRS and/or satellite communication.
7. The intelligent control system of the station according to claim 1, wherein the department management is used for maintaining department information and supporting creation of multi-level departments, the user management is used for uniformly managing system users of all departments, adding, modifying, deleting and resetting passwords of user information and configuring roles and posts of the users, the role management is used for uniformly managing roles of the users, establishing authority relation between the roles and function menus and function buttons, carrying out function authorization on the users through the roles, and the post management is used for uniformly managing posts of the users and supporting addition, modification and deletion of post information.
8. The intelligent control system of claim 1, wherein the device information management performs operations of adding, modifying and deleting device information in the system, provides an overview list of the device information, supports querying the device information according to various condition combinations, and the device group has a user-defined device group function, and can user-define a group name.
9. The intelligent station control system according to claim 1, wherein the station overview is used for checking station real-time data, the station archive management is used for station management personnel to maintain basic archive information of station, the line management is used for maintaining and managing line information of the station, one-to-many relation of the station and the line is supported, line export equipment can be bound, the station is configured to be used for station real-time monitoring to perform display effect configuration, configuration/3D pictures of the station are uploaded through the function, the station equipment is deployed into the pictures according to actual conditions to achieve display effect of station real-time monitoring, real-time data is used for realizing real-time monitoring of station information through the Internet of things equipment, equipment and degree information of the station is displayed at corresponding positions according to the station configuration, threshold configuration can be performed on monitoring equipment, alarm information can be pushed in time when the monitoring data exceeds a corresponding threshold range, management functions of the station early warning information are supported, list query and processing content can be processed and recorded on the early warning information, historical data are provided to be used for inquiring the early warning information in a list, the early warning equipment can be queried in a list form of time, the early warning information can be queried in the form of two-year, the early warning data is queried, and the historical data can be queried in the form of the history data is queried according to the different types of the early warning data.
10. The intelligent control method of a station according to claim 1, characterized by comprising the intelligent control system of a station according to any one of claims 1-9, comprising the steps of: the data acquisition module acquires relevant operation data from equipment through a sensor, a ‌ metering device, ‌ image acquisition equipment, ‌ sound acquisition equipment, ‌ GPS positioning equipment, ‌ RFID tag equipment, ‌ data acquisition terminal, ‌ smart phone and handheld terminal; Analyzing and processing the collected data by using a fault diagnosis module, diagnosing and positioning the equipment fault cause by ‌ and combining a preset fault model and algorithm ‌, wherein the fault model comprises a support vector machine, a decision tree, a random forest or a neural network, and the mathematical model formula of the support vector machine is as follows , Representing a decision function, Is a parameter of a support vector machine, Is a sample label, Is a kernel function, b is an offset, x is an input vector, and the decision tree mathematical model formula is if Wherein Is an input variable, Is an output variable, Representing category, c representing category number, and a random forest mathematical model formula is , Representing the predicted result of the random forest on the input data x, Representing the number of decision trees in a random forest, Represent the first The result of the prediction of the decision tree is expressed as a neural network formula , Representing the output of neurons, Representing an activation function, Represent the first The weight of each input signal, Represent the first The method for diagnosing the faults comprises the steps of diagnosing based on rules, diagnosing driven by ‌ models and diagnosing based on data mining, presetting a solution and suggestion library in a solution module, providing corresponding solutions and suggestions according to fault diagnosis results ‌, providing ‌ for users to refer to and take corresponding repairing measures, and establishing the fault models, wherein the method comprises the following steps of: (1) Collecting data; (2) Cleaning and preprocessing data; (3) Selecting a feature related to the fault from the preprocessed data as an input variable; (4) Training by using the selected characteristics and known fault data through a machine learning algorithm to obtain a model for predicting fault occurrence; (5) Verifying the trained model, and evaluating the prediction effect of the model on new data; (6) Setting a corresponding early warning threshold value; (7) The trained model is applied to actual equipment, so that real-time monitoring is realized; (8) Updating and optimizing the model regularly; The control module is used for executing control instructions to adjust the running state of the equipment, and comprises a programmable logic controller and a remote terminal unit, wherein the data storage processing module is used for storing and processing collected data, comprises a database and a data server, and has the functions of data storage and management, data inquiry, data processing, data safety, data backup and recovery, concurrent control and transaction management, the communication module is used for realizing data transmission between internal and external equipment, the communication module comprises wired communication and wireless communication, wherein the wired communication adopts Ethernet and/or optical fiber, the wireless communication adopts GPRS and/or satellite communication, and the man-machine interface is used for interaction between operators and comprises a display screen, a control panel and a touch screen; The field control station is responsible for monitoring and controlling various devices and processes in the field station in real time, document management is used for sorting, ‌ summarizing and counting various document materials generated in the whole life cycle of the device, ‌ is used for supporting the intensive inquiry and browsing of documents, ‌ is multi-layered and ‌ is used for different structures, and hardware devices comprise, but are not limited to, a converter valve, a ‌ direct current filter and an alternating current filter; The emergency shutdown ‌ is immediately and emergently shut down ‌ when a serious accident occurs in a station or a downstream pipeline, ‌ separates the upper pipeline and the ‌ downstream pipeline from the station, ‌ is used for reducing the loss of natural gas in an accident state and protecting the safety of the station, the emergency shutdown valve ‌ is matched with the emergency shutdown, ‌ is used for realizing quick shutdown by an electric actuator, ‌ is used for preventing the expansion of the accident, the electric actuator is powered by an uninterruptible power supply device ‌, ‌ ensures that the electric actuator can still operate under the condition of power failure, ‌ ensures the normal operation of the emergency shutdown valve, and the uninterruptible power supply device ‌ provides continuous power supply for the electric actuator, and ‌ ensures the reliable operation under the emergency condition; Step six, system management comprises department management, user management, role management and post management; the equipment management comprises equipment information management and equipment grouping, station management comprises station overview, station archive management, line management, station configuration, real-time data, early warning data and historical data, remote control is used for controlling the opening or closing of equipment, department management is used for maintaining department information and supporting the creation of multi-level departments, user management is used for carrying out unified management on system users of all departments, adding, modifying, deleting and password resetting of user information and configuring roles and posts of the users, role management is used for carrying out unified management on the roles of the users, establishing authority relation between roles and function menus and function buttons, carrying out function authorization on the users through the roles, station management is used for carrying out unified management on the posts of the users, supporting the new adding, modifying and deleting of station information, carrying out new adding, modifying and deleting operation on the equipment information in a system, providing an overview list of the equipment information and supporting the combination inquiry of the equipment information according to various conditions, the equipment grouping is provided with a self-defined equipment grouping function, the user can be used for checking the real-time data of the stations, the station archive management is used for carrying out unified management on roles of the users, the functions of the stations are authorized functions of the stations, the management personnel maintain the stations, the line management is used for carrying out the configuration of the stations, the line management station management is used for carrying out real-time data, the line configuration and the line management station configuration is carried out the line configuration and the station management station has 3, and the real-time file configuration effect can be carried out, and the real-time management station configuration and has the effect is configured and has the function of the functions, the method comprises the steps of arranging station equipment in a diagram according to actual conditions to achieve a display effect of station real-time monitoring, realizing real-time monitoring of station information by using the Internet of things equipment, displaying a station effect diagram according to station configuration, displaying equipment and equipment degree information at corresponding positions, performing threshold configuration on monitoring equipment, pushing alarm information timely when the monitoring data exceeds a corresponding threshold range, providing a management function for the station early warning information by early warning data, supporting list query of the early warning information, processing and recording the early warning information, providing station historical data query of four time latitudes of 'time', 'day', 'month' and 'year' by using historical data, and displaying query results in two forms of a graph and a list.

Description

Intelligent control system and control method for station Technical Field The invention relates to the technical field of intelligent control of stations, in particular to an intelligent control system and an intelligent control method of stations. Background The main uses of the station are centralized processing, ‌ storage, ‌ distribution and transportation of oil and gas, which mainly comprises oil and gas centralized processing, ‌ oilfield water injection, ‌ sewage processing, ‌ power supply and transformation, auxiliary production facilities and the like, wherein the oil and gas centralized processing comprises crude oil dehydration, ‌ desalination, ‌ natural gas purification, ‌ crude oil stabilization, ‌ light hydrocarbon, ‌ liquefied gas recovery and the like, and the ‌ station is a central hub for oilfield crude oil centralized transportation and processing. Along with the continuous increase of the economy in China, the energy demand is continuously increased, the oil-gas station is taken as an important link of energy supply, the safety, high efficiency and environment protection management of the oil-gas station become urgent, the traditional oil-gas station does not have the functions of equipment fault self-detection, module linkage control, intelligent flow switching and emergency parking intelligent regulation and control, workers are required to regularly carry out inspection and monitor abnormal conditions in cooperation with intelligent monitoring equipment, more workers are required, the automation degree of the control of the station is low, and the development demands of modernization and informatization are difficult to meet. Therefore, the intelligent control system and the intelligent control method for the station can be designed aiming at the problem of low automation degree of the control of the station. Disclosure of Invention To overcome the problem of low automation of the control of the station. The intelligent control system of the station comprises equipment fault self-detection, module linkage control, intelligent flow switching, intelligent emergency stop regulation and control and management; The equipment fault self-checking comprises a data acquisition module, a fault diagnosis module and a solution module, wherein the data acquisition module acquires relevant operation data from equipment through the acquisition equipment, the fault diagnosis module analyzes and processes the acquired data, ‌ is combined with a preset fault model and algorithm, ‌ is used for diagnosing and positioning equipment fault reasons, the fault model comprises a support vector machine, a decision tree, a random forest or a neural network, and the mathematical model formula of the support vector machine is as follows ,Representing a decision function,Is a parameter of a support vector machine,Is a sample label,Is a kernel function, b is an offset, x is an input vector, and the decision tree mathematical model formula is ifWhereinIs an input variable,Is an output variable,Representing category, c representing category number, and a random forest mathematical model formula is,Representing the predicted result of the random forest on the input data x,Representing the number of decision trees in a random forest,Represent the firstThe result of the prediction of the decision tree is expressed as a neural network formula,Representing the output of neurons,Representing an activation function,Represent the firstThe weight of each input signal,Represent the firstThe fault diagnosis method comprises rule-based diagnosis, ‌ model-driven diagnosis and data mining-based diagnosis, and a solution and suggestion library is preset in the solution module, and corresponding solutions and suggestions are provided according to the fault diagnosis result ‌, and ‌ are provided for users to refer to and take corresponding repair measures. The module linkage control comprises a control module, a data storage processing module, a communication module and a human-computer interface, wherein the control module is used for executing control instructions to adjust the running state of equipment, the data storage processing module is used for storing and processing collected data, and comprises a database and a data server, the communication module is used for realizing data transmission between internal equipment and external equipment, and the human-computer interface is used for interaction between operators and the equipment and comprises a display screen, a control panel and a touch screen; The intelligent flow switching comprises a field control station, a document management and hardware equipment, wherein the field control station is responsible for monitoring and controlling various equipment and flows in the field station in real time, the document management is used for sorting, ‌ induction and statistics of various document materials generated in the whole life cycle of equipment, ‌ supports the inquiry and brows